TY - GEN
T1 - On the Globalization of the QAnon Conspiracy Theory Through Telegram
AU - Hoseini, Mohamad
AU - Melo, Philipe
AU - Benevenuto, Fabricio
AU - Feldmann, Anja
AU - Zannettou, Savvas
PY - 2023
Y1 - 2023
N2 - QAnon is a far-right conspiracy theory that has implications in the real world, with supporters of the theory participating in real-world violent acts like the US capitol attack in 2021. At the same time, the QAnon theory started evolving into a global phenomenon by attracting followers across the globe and, in particular, in Europe, hence it is imperative to understand how QAnon has become a worldwide phenomenon and how this dissemination has been happening in the online space. This paper performs a large-scale data analysis of QAnon through Telegram by collecting 4.4M messages posted in 161 QAnon groups/channels. Using Google's Perspective API, we analyze the toxicity of QAnon content across languages and over time. Also, using a BERT-based topic modeling approach, we analyze the QAnon discourse across multiple languages. Among other things, we find that the German language is prevalent in our QAnon dataset, even overshadowing English after 2020. Also, we find that content posted in German and Portuguese tends to be more toxic compared to English. Our topic modeling indicates that QAnon supporters discuss various topics of interest within far-right movements, including world politics, conspiracy theories, COVID-19, and the anti-vaccination movement. Taken all together, we perform the first multilingual study on QAnon through Telegram and paint a nuanced overview of the globalization of QAnon.
AB - QAnon is a far-right conspiracy theory that has implications in the real world, with supporters of the theory participating in real-world violent acts like the US capitol attack in 2021. At the same time, the QAnon theory started evolving into a global phenomenon by attracting followers across the globe and, in particular, in Europe, hence it is imperative to understand how QAnon has become a worldwide phenomenon and how this dissemination has been happening in the online space. This paper performs a large-scale data analysis of QAnon through Telegram by collecting 4.4M messages posted in 161 QAnon groups/channels. Using Google's Perspective API, we analyze the toxicity of QAnon content across languages and over time. Also, using a BERT-based topic modeling approach, we analyze the QAnon discourse across multiple languages. Among other things, we find that the German language is prevalent in our QAnon dataset, even overshadowing English after 2020. Also, we find that content posted in German and Portuguese tends to be more toxic compared to English. Our topic modeling indicates that QAnon supporters discuss various topics of interest within far-right movements, including world politics, conspiracy theories, COVID-19, and the anti-vaccination movement. Taken all together, we perform the first multilingual study on QAnon through Telegram and paint a nuanced overview of the globalization of QAnon.
KW - QAnon
KW - social media
KW - Telegram
KW - topic modeling
KW - toxicity analysis
UR - http://www.scopus.com/inward/record.url?scp=85150966622&partnerID=8YFLogxK
U2 - 10.1145/3578503.3583603
DO - 10.1145/3578503.3583603
M3 - Conference contribution
AN - SCOPUS:85150966622
T3 - ACM International Conference Proceeding Series
SP - 75
EP - 85
BT - WebSci 2023 - Proceedings of the 15th ACM Web Science Conference
PB - ACM
T2 - 15th ACM Web Science Conference, WebSci 2023
Y2 - 30 April 2023 through 1 May 2023
ER -